Mountain Lakes, NJ
Mountain Lakes wildfire risk explained
USFS scores Mountain Lakes at the 28th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,747 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Mountain Lakes at the 28th percentile, close to its 28th-percentile risk score.
Mountain Lakes's building exposure, zone by zone
1,747 buildings are counted in Mountain Lakes, and 92.2% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0.3% rated Minimal.
How Mountain Lakes compares
There's little gap between Mountain Lakes's 28th national percentile and its 23rd percentile inside New Jersey, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Mountain Lakes ranks 22,661 for wildfire risk (1 is highest) and 8,237 by building count (1 is largest). Within New Jersey alone, it ranks 543 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Mountain Lakes and the insurance market
At the 28th national percentile, Mountain Lakes rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Mountain Lakes (92.2%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Mountain Lakes's figures come from
Mountain Lakes's 28th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Mountain Lakes's dominant direct exposure actually means, with real examples from across the dataset.